Modelling and targeting differentiation-state heterogeneity in cancer


Session type:

Piyush Gupta1
1Whitehead Institute for Biomedical Research, Cambridge, MA, USA


Cancer cells within individual tumors often exist in distinct phenotypic states that differ in their functional attributes. For example, carcinoma cells that have undergone an epithelial-to-mesenchymal transition (EMT) are invasive and metastatic, while cells that exhibit stem-like features (CSCs) fuel tumor formation recurrence and resistance to therapy. Based on a recently-reported link between EMT and CSCs, we have a developed a high-throughput screening strategy for the identification of compounds that are toxic to CSCs. We present our screening results, as well as follow-up strategies to use EMT-selective chemical probes to uncover novel insights into EMT/CSC biology.

While cancer cells can be experimentally induced into EMT, yielding purely mesenchymal populations, cancer cell populations within tumors are generally phenotypically heterogeneous. To understand the mechanisms that contribute to this cellular diversity, we examined stem-like, luminal and basal/mesenchymal states in breast cancer cell lines. We observed that cancer cells interconvert between phenotypic states in culture. Using a Markov model of cell-state transitions, we demonstrate that interconversion between states is sufficient to promote a stable equilibrium in cell-state proportions. A prediction of the Markov model is that any sorted subpopulation will eventually return to equilibrium cell-state proportions, provided that interconversion occurs between all states. Additionally, quantification of interconversion rates facilitates the interpretation of genetic and chemical perturbation experiments in which cell-state proportions are measured at a population level. Collectively, these findings contribute to our understanding of cancer cell heterogeneity and cell-state dynamics, and demonstrate how chemical compounds can be discovered that target specific cell states.